Microsoft Power BI and Excel remain the most widely used analytics tools in the enterprise. But when they connect directly to cloud data platforms, teams often encounter familiar limits: slow performance at scale, duplicated extracts, inconsistent metrics, and increasing dependence on IT.
Organizations evaluating Microsoft Fabric face a difficult decision: rebuild their analytics stack on a new proprietary platform or modernize what already works.
In this joint webinar, AtScale and Snowflake demonstrate how a universal semantic layer allows Power BI and Excel users to work directly on governed, high-performance data directly in Snowflake, without sacrificing flexibility, control, or existing investments.
You’ll See How:
- Power BI and Excel connect live to Snowflake using native DAX and MDX, PivotTables, and Cube Functions, without extracts or duplicated datasets
- Intelligent aggregates and caching deliver sub-second queries while reducing overall TCO
- Metrics are defined once and reused consistently across teams, dashboards, and reports
- Row-level security and role-based access control are enforced centrally, not recreated in every BI tool
- Open, vendor-neutral semantics keep definitions portable across Snowflake, Power BI, Excel, and AI workloads
What You’ll Learn
- Why direct-to-warehouse BI often degrades as user concurrency increases
- How a universal semantic layer improves performance without requiring migration to Microsoft Fabric
- How governed self-service analytics reduces IT bottlenecks while preserving control
- How enterprises modernize analytics on Snowflake while lowering total cost of ownership
If you’re supporting large Power BI and Excel workloads on Snowflake, working to standardize business metrics, or looking to improve performance without rebuilding your platform, this session provides a practical blueprint for scaling self-service analytics without losing governance or control.
